Predictive Analytics in Commerce

Predictive Analytics in Commerce

More Personal to the Customer

Step 1. Build the best possible model

Nienke suggested that you try to build your own cross-sell models for the other products you want to include in the next best offer. Try to first build a couple of trees – or more if you are getting the hang of it!

After you created different decision trees, work with the rank or index method based on your predicted probabilities to determine the next best offer. (Hint: If you need a little help with these methods, check out the additional material section in the previous unit).

Step 2. Inform your colleagues

Use your model outcomes in a briefing to your colleagues. You want to activate them by showing them the new way of using predictive modelling to derive the Next Best Offer per customer. In this way your company can be more relevant - and thus personal - to the customer. Take them through the most important process-steps.

Next best offer - Home Active

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I've created a model for NBO based on HomeActive variable.
I found Decision Tree model to be quite intuitive and relatively easier to explain to eventual decision makers in a company. One of the takeaways from my test one could then conclude that customer who also possess Accident Insurance would be more inclined to acquire Home Insurance.

As a side note during my tests, I had to try to run the same model several times before getting the hang of it, there was something in my coding that wasn't producing the results correctly, ie: the decision tree was showing only two nods regardless of what tried, and I tried with many different variables. I had to start a whole new "script" to make sure all my data input was correct.